The present study aims at insights into the nature of incremental learning in the context of Gold’s model of identification in the limit. With a focus on natural requirements s...
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
Abstract. We consider the problem of sequence prediction in a probabilistic setting. Let there be given a class C of stochastic processes (probability measures on the set of one-wa...
Due to the various and dynamic nature of stimuli, decisions of intelligent agents must rely on the coordination of complex cognitive systems. This paper precisely focusses on a gen...
This paper describes an approach to automatically learn planning operators by observing expert solution traces and to further refine the operators through practice in a learning-b...